What is Data warehouse?

A data warehouse is a database that brings a company's data from different systems together in one place, in an organized structure, for analysis and reporting. In marketing, it is where ad platform, analytics, CRM and sales data are combined; Google BigQuery, Snowflake and Amazon Redshift are common examples.

Last updated: 20 October 2026View as Markdown

In short

A data warehouse gives marketing a single source of truth by combining data that ad platforms, GA4 and the CRM each report under their own definitions. Teams can trace which campaign brought which lead and which lead became a sale in one place, free of the retention and sampling limits of platform interfaces. Data is loaded on a schedule with ETL or ELT tools and queried in SQL. A company exporting GA4 data to BigQuery can join ad spend with CRM revenue to calculate true profitability by channel.

Key points

A data warehouse gathers data from different systems in one place for analysis and reporting.
In marketing, ad, analytics, CRM and sales data are combined in a shared model.
Google BigQuery, Snowflake and Amazon Redshift are common examples.
A warehouse holds structured, modeled data, while a data lake stores raw data in any format.
It removes the retention and sampling limits of ad and analytics platform interfaces.

The data warehouse in marketing

Ad platforms, GA4 and the CRM each report their own data by their own definitions. A data warehouse combines this data in a shared model: which campaign brought which lead, and which lead brought which sale. Reports and analyses are fed from this single source.

Data warehouse vs. data lake

A data warehouse holds structured data modeled for analysis; a data lake stores raw data in any format. For marketing reporting, a data warehouse is usually enough.

Why it matters

It gives you a single source, consistent metrics and fast reporting, and removes the retention and sampling limits of platform interfaces. Setup: marketing data warehouse.

Last updated: 20 October 2026